Recent advances of deep learning for spectral snapshot compressive imaging

Jinli Suo; Zongliang Wu; Zhangyuan Li; Xin Yuan

doi:10.1117/12.2641748

4 January 2023 Recent advances of deep learning for spectral snapshot compressive imaging

Jinli Suo, Zongliang Wu, Zhangyuan Li, Xin Yuan

Proceedings Volume 12317, Optoelectronic Imaging and Multimedia Technology IX; 1231702 (2023) https://doi.org/10.1117/12.2641748
Event: SPIE/COS Photonics Asia, 2022, Online Only

Abstract

We review the recent deep learning reconstruction algorithms for spectral snapshot compressive imaging (SCI), which used a single shot measurement to capture the three-dimensional (3D, x, y, λ) spectral image. Recent years, deep learning has been the dominant algorithm to conduct reconstruction due to high speed and accuracy. Various frameworks such as end-to-end neural networks, deep unfolding, plug-and-play networks have been developed. Furthermore, the untrained neural networks have also been used. In this paper, we review diverse deep learning methods for spectral SCI. In addition to the aforementioned frameworks, different backbones and network structures including the most recent Transformers are reviewed. Simulation and real data results are presented to compare these methods.

Conference Presentation

Citation Download Citation

Jinli Suo, Zongliang Wu, Zhangyuan Li, and Xin Yuan "Recent advances of deep learning for spectral snapshot compressive imaging", Proc. SPIE 12317, Optoelectronic Imaging and Multimedia Technology IX, 1231702 (4 January 2023); https://doi.org/10.1117/12.2641748

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